Data sourced from Dakota Marketplace, the global LP and GP intelligence platform trusted by thousands of investment professionals. Learn More | Book a Demo
AI tools like Claude and ChatGPT can now connect directly to databases… and for anyone working in private markets, that's a major unlock.
But only if you're actually using it.
The professionals pulling ahead right now aren't waiting for AI to become part of their firm's official process. They're building it into their daily workflow today whether for meeting prep, prospect research, outreach, or competitive intelligence.
The difference between a generic AI tool and the Claude App connected to Dakota Marketplace is the difference between a guess and a grounded answer.
Generic AI has no access to 30 years of verified LP, GP, fund, and transaction data. It hallucinates. It generalizes.
Dakota Marketplace’s Claude App doesn't return rows. It returns intelligence, built on the only dataset built exclusively for the private markets community.
Here's what that looks like in practice, five things we learned today.
1. The Australian Industry Super Fund Infrastructure List
For: Heads of international distribution at global infrastructure equity and debt funds The Job: Targeting Australian industry super funds with large, growing infrastructure allocation targets
The prompt
I'm raising capital from Australian institutional investors for a global infrastructure strategy. Using Dakota Marketplace and web research, identify Australian industry superannuation funds with AUM above AUD $50B that have an infrastructure allocation target above 10%, showing current allocation vs. target, the fund's head of infrastructure or real assets, and any recent commitments to non-Australian infrastructure managers.
2. The State University System Consolidated Endowment List
For: Directors of capital formation at real assets and private equity funds The Job: Targeting consolidated, multi-campus university endowment pools rather than individual campus endowments
The prompt
Using Dakota Marketplace, identify consolidated state university system endowment pools (managing multiple campuses under one investment office) with $2B+ in pooled assets and a documented real assets or private equity allocation. Show pooled AUM, current allocation percentage and target, the CIO or chief investment officer contact, and any recent manager commitments in real assets.
These prompts are only as good as the data behind them. Every prompt above runs on Dakota Marketplace data: the verified contacts, AUM, investment preferences, and transaction activity that turn a generic AI answer into a real prospect list. Whichever AI app you use, the facts come from the same place. Book a demo of Dakota Marketplace to get connected.
3. The Insurance Fund-of-One / SMA Private Credit List
For: Managing directors at private credit managers building an insurance-dedicated platform The Job: Identifying insurers open to a bespoke separately managed account rather than a commingled fund commitment
The prompt
I'm building out a fund-of-one and SMA platform for insurance clients in our private credit strategy. Using Dakota Marketplace, identify insurance companies with $3B+ in invested assets that have an existing separately managed account or fund-of-one relationship with an asset manager (in any asset class), showing invested assets, current SMA/fund-of-one providers, key investment contact, and stated preference for customized versus commingled structures.
4. The Corporate DB Plan Pre-Termination List
For: Distribution teams at return-seeking private credit and equity strategies The Job: Identifying corporate DB plans mid-way through a buyout/annuitization process that still hold return-seeking assets in the interim
The prompt
I want to target corporate defined benefit plans that have announced intent to pursue a full plan termination or buyout but haven't yet completed it, since they often still hold return-seeking assets in the interim. Using Dakota Marketplace and web research, identify corporate DB plans with $1B+ AUM that have publicly disclosed a buyout or annuitization process underway in the last 18 months. Show plan AUM, current funded status, plan sponsor treasurer or CFO contact, and current allocation to return-seeking assets.
5. The Corporate Foundation Private Equity List
For: Fundraisers at growth equity and buyout funds The Job: Identifying company-sponsored corporate foundations with an endowment pool allocating to private equity
The prompt
Using Dakota Marketplace, identify corporate-sponsored foundations (charitable foundations funded and governed by a public company) with $500M+ in endowment assets that have a documented private equity or alternatives allocation. Show endowment AUM, PE allocation percentage, foundation president or investment committee contact, and any recent commitments to outside PE managers.
Start Prompting With Real Data
Here's the thing that makes these prompts work… on its own, AI is brilliant at structure and terrible at facts it doesn't have. Ask any chatbot for a pension fund's current allocation, a CIO's contact, or who actually owns a target company, and it will confidently make something up.
That's the whole reason these prompts run on Dakota Marketplace data, no matter which AI app you prefer: you get the speed and structure of AI with contacts, AUM, allocations, and transactions that are actually verified.
AI is the engine. Dakota Marketplace is the fuel.
Connect the two, in Claude, ChatGPT, or whatever you already use, and the work that used to eat your morning takes minutes, with data you can actually act on.
Book a demo of Dakota Marketplace to get started.
